class ComponentWithDerivatives(Component):
"""This is the base class for all objects containing Traits that are \
accessible to the OpenMDAO framework and are "runnable."
"""
def __init__(self, *args, **kwargs):
""" Only one thing to do: create Derivatives object."""
self.derivatives = Derivatives(self)
super(ComponentWithDerivatives, self).__init__(*args, **kwargs)
def _execute_ffd(self, ffd_order):
"""During Fake Finite Difference, instead of executing, a component
can use the available derivatives to calculate the output efficiently.
Before FFD can execute, calc_derivatives must be called to save the
baseline state and the derivatives at that baseline point.
This method approximates the output using a Taylor series expansion
about the saved baseline point.
ffd_order: int
Order of the derivatives to be used (typically 1 or 2).
"""
for name in self.derivatives.out_names:
setattr(self, name,
self.derivatives.calculate_output(name, ffd_order))
def calc_derivatives(self, first=False, second=False):
"""Prepare for Fake Finite Difference runs by calculating all needed
derivatives, and saving the current state as the baseline. The user
must supply calculate_first_derivatives() and/or
calculate_second_derivatives() in the component.
This function should not be overriden.
first: Bool
Set to True to calculate first derivatives.
second: Bool
Set to True to calculate second derivatives.
"""
savebase = False
# Calculate first derivatives in user-defined function
if first and hasattr(self, 'calculate_first_derivatives'):
self.calculate_first_derivatives()
self.derivative_exec_count += 1
savebase = True
# Calculate second derivatives in user-defined function
if second and hasattr(self, 'calculate_second_derivatives'):
self.calculate_second_derivatives()
self.derivative_exec_count += 1
savebase = True
# Save baseline state
if savebase:
self.derivatives.save_baseline(self)
def check_derivatives(self, order, driver_inputs, driver_outputs):
"""Calls the validate method of the derivatives object in order to
warn the user about all missing derivatives."""
local_inputs = []
for item in driver_inputs:
if isinstance(item, tuple):
for linked_item in item:
paths = linked_item.split('.', 1)
if paths[0] == self.name:
local_inputs.append(paths[1])
else:
paths = item.split('.', 1)
if paths[0] == self.name:
local_inputs.append(paths[1])
local_outputs = []
for item in driver_outputs:
if isinstance(item, tuple):
for linked_item in item:
paths = linked_item.split('.', 1)
if paths[0] == self.name:
local_outputs.append(paths[1])
else:
paths = item.split('.', 1)
if paths[0] == self.name:
local_outputs.append(paths[1])
self.derivatives.validate(order, local_inputs, local_outputs)
class ComponentWithDerivatives (Component):
"""This is the base class for all objects containing Traits that are \
accessible to the OpenMDAO framework and are "runnable."
"""
def __init__(self, *args, **kwargs):
""" Only one thing to do: create Derivatives object."""
self.derivatives = Derivatives(self)
super(ComponentWithDerivatives, self).__init__(*args, **kwargs)
def _execute_ffd(self, ffd_order):
"""During Fake Finite Difference, instead of executing, a component
can use the available derivatives to calculate the output efficiently.
Before FFD can execute, calc_derivatives must be called to save the
baseline state and the derivatives at that baseline point.
This method approximates the output using a Taylor series expansion
about the saved baseline point.
ffd_order: int
Order of the derivatives to be used (typically 1 or 2).
"""
for name in self.derivatives.out_names:
setattr(self, name,
self.derivatives.calculate_output(name, ffd_order))
def calc_derivatives(self, first=False, second=False):
"""Prepare for Fake Finite Difference runs by calculating all needed
derivatives, and saving the current state as the baseline. The user
must supply calculate_first_derivatives() and/or
calculate_second_derivatives() in the component.
This function should not be overriden.
first: Bool
Set to True to calculate first derivatives.
second: Bool
Set to True to calculate second derivatives.
"""
savebase = False
# Calculate first derivatives in user-defined function
if first and hasattr(self, 'calculate_first_derivatives'):
self.calculate_first_derivatives()
savebase = True
# Calculate second derivatives in user-defined function
if second and hasattr(self, 'calculate_second_derivatives'):
self.calculate_second_derivatives()
savebase = True
# Save baseline state
if savebase:
self.derivatives.save_baseline(self)
def check_derivatives(self, order, driver_inputs, driver_outputs):
"""Calls the validate method of the derivatives object, in order to
warn the user about all missing derivatives."""
local_inputs = []
for item in driver_inputs:
if isinstance(item, tuple):
for linked_item in item:
paths = linked_item.split('.',1)
if paths[0] == self.name:
local_inputs.append(paths[1])
else:
paths = item.split('.',1)
if paths[0] == self.name:
local_inputs.append(paths[1])
local_outputs = []
for item in driver_outputs:
if isinstance(item, tuple):
for linked_item in item:
paths = linked_item.split('.',1)
if paths[0] == self.name:
local_outputs.append(paths[1])
else:
paths = item.split('.',1)
if paths[0] == self.name:
local_outputs.append(paths[1])
self.derivatives.validate(order, local_inputs, local_outputs)
def __init__(self, *args, **kwargs):
""" Only one thing to do: create Derivatives object."""
self.derivatives = Derivatives(self)
super(ComponentWithDerivatives, self).__init__(*args, **kwargs)
def __init__(self, *args, **kwargs):
""" Only one thing to do: create Derivatives object."""
self.derivatives = Derivatives(self)
super(ComponentWithDerivatives, self).__init__(*args, **kwargs)